article · 2021
Targets Detection Using Multiple Foveas
Petrucio R. T. Medeiros, Rafael B. Gomes, Luiz Marcos Garcia Gonçalves
Cited by 0Abstract and details only
Abstract
Target detection enables running a robotic task. However, their limited resources make large amount of data processing harder. Image foveation is an approach that can reduce processing demand by reducing the amount of data to be processed. However, as an important visual stimulli can be attenuated by this reduction, some strategy should be applied in order to keep/recover awareness of it. This work compares gradient descent (potential field), maximum likelihood, multilateration, trilateration, and barycentric coordinates to solve this problem in a multiple dynamic and fixed foveas context. Our results demonstrate that the proposed methodology detects the target converging with an average euclidian distance of 51 pixels from the target’s center position.
Cite this paper
Medeiros, P. R. T., Gomes, R. B., & Gonçalves, L. M. G. (2021). Targets Detection Using Multiple Foveas. https://doi.org/10.1109/lars/sbr/wre54079.2021.9605452
Medeiros, Petrucio R. T., et al. “Targets Detection Using Multiple Foveas.” vol. 1, 2021, pp. 264–69, https://doi.org/10.1109/lars/sbr/wre54079.2021.9605452.
Medeiros, Petrucio R. T., Rafael B. Gomes, and Luiz Marcos Garcia Gonçalves. 2021. “Targets Detection Using Multiple Foveas.” https://doi.org/10.1109/lars/sbr/wre54079.2021.9605452.
Medeiros, P.R.T., Gomes, R.B. and Gonçalves, L.M.G. (2021) ‘Targets Detection Using Multiple Foveas’. Available at: https://doi.org/10.1109/lars/sbr/wre54079.2021.9605452.
@article{medeiros2021targets,
title = {{Targets Detection Using Multiple Foveas}},
author = {Medeiros, Petrucio R. T. and Gomes, Rafael B. and Gonçalves, Luiz Marcos Garcia},
volume = {1},
pages = {264--269},
year = {2021},
doi = {10.1109/lars/sbr/wre54079.2021.9605452}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.